Brain MRI artefact detection and correction using convolutional neural networks

Öksüz İ.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, vol.199, 2021 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 199
  • Publication Date: 2021
  • Doi Number: 10.1016/j.cmpb.2020.105909
  • Journal Name: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Applied Science & Technology Source, BIOSIS, Biotechnology Research Abstracts, Compendex, Computer & Applied Sciences, EMBASE, INSPEC, MEDLINE
  • Keywords: Brain MRI, Artefact detection, Convolutional neural networks, Stroke segmentation
  • Istanbul Technical University Affiliated: Yes

Abstract

Background and Objective: Brain MRI is one of the most commonly used diagnostic imaging tools to detect neurodegenerative disease. Diagnostic image quality is a key factor to enable robust image analysis algorithms developed for downstream tasks such as segmentation. In clinical practice, one of the main challenges is the presence of image artefacts, which can lead to low diagnostic image quality.